Quality improvement methods are essential to gathering high-quality crowdsourced data,
both for research and industry applications. A popular and broadly applicable method is task …

With the widespread deployment of data-driven services, the demand for data volumes
continues to grow. At present, many applications lack reliable human supervision in the …

Mobile crowdsensing (MCS) can promote data acquisition and sharing among mobile
devices. Traditional MCS platforms are based on a triangular structure consisting of three …

Crowdsourcing is a paradigm that provides a cost-effective solution for obtaining services or
data from a large group of users. It is increasingly being used in modern society for data …

As an effective way to solicit useful information from the crowd, crowdsourcing has emerged
as a popular paradigm to solve challenging tasks. However, the data provided by the …

Mobile network operators (MNO) can opportunistically use the licensed bands of the primary
users (PU) provided that they monitor the spectrum and stop their transmission upon …

Crowdsourcing is an information system for recruiting online workers to perform human
intelligent tasks (HITs) that are hard for computers. Due to the openness of crowdsourcing …

Researchers continue to focus on privacy-preserving truth discovery and achieve certain
results with the increasingly popular trend of privacy protection. However, the common …

Understanding the vulnerability of label aggregation against data poisoning attacks is key to
ensuring data quality in crowdsourced label collection. State-of-the-art attack mechanisms …

Crowdsourced entity collection leverages human's ability to collect entities that are missing
in a database, which has many real-world applications, such as knowledge base enrichment …